4.8 Article

Intelligent SERS Navigation System Guiding Brain Tumor Surgery by Intraoperatively Delineating the Metabolic Acidosis

Journal

ADVANCED SCIENCE
Volume 9, Issue 7, Pages -

Publisher

WILEY
DOI: 10.1002/advs.202104935

Keywords

artificial intelligence; brain tumor; metabolic acidosis; surface enhanced Raman spectroscopy; surgery navigation system

Funding

  1. National Key Research & Development Project
  2. Ministry of Science and Technology of China [2018YFE0118800]
  3. Shanghai Municipal Science and Technology Major Project [2018SHZDZX01]
  4. Program of Shanghai Science and Technology Committee [18441900600, 19431900400, 20ZR1407800]
  5. National Science Fund for Distinguished Young Scholars [82025019]
  6. National Natural Science Foundation of China [81771895, 91959127, 92159304, 81873893]
  7. Shanghai Center for Brain Science and Brain-Inspired Technology, Double First-Class initiative of Fudan University [IDH1232075]

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This article reports an intelligent surface-enhanced Raman scattering navigation system that can delineate the acidic margins of gliomas without using exogenous probes. The system uses a homemade deep learning model to process Raman spectra and quickly delineate the pH map of the tumor resection bed. Experimental results demonstrate a significant improvement in overall survival rate of animal models after surgery guided by this system.
Surgeons face challenges in intraoperatively defining margin of brain tumors due to its infiltrative nature. Extracellular acidosis caused by metabolic reprogramming of cancer cells is a reliable marker for tumor infiltrative regions. Although the acidic margin-guided surgery shows promise in improving surgical prognosis, its clinical transition is delayed by having the exogenous probes approved by the drug supervision authority. Here, an intelligent surface-enhanced Raman scattering (SERS) navigation system delineating glioma acidic margins without administration of exogenous probes is reported. With assistance of this system, the metabolites at the tumor cutting edges can be nondestructively transferred within a water droplet to a SERS chip with pH sensitivity. Homemade deep learning model automatically processes the Raman spectra collected from the SERS chip and delineates the pH map of tumor resection bed with increased speed. Acidity correlated cancer cell density and proliferation level are demonstrated in tumor cutting edges of animal models and excised tissues from glioma patients. The overall survival of animal models post the SERS system guided surgery is significantly increased in comparison to the conventional strategy used in clinical practice. This SERS system holds the promise in accelerating clinical transition of acidic margin-guided surgery for solid tumors with infiltrative nature.

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